


How to Serve Custom HTML Files Instead of index.html in FastAPI's Root Path?
Serving Custom HTML Files Instead of Index.html in FastAPI Root Path
In FastAPI, you can serve static files, including HTML, using the StaticFiles middleware. However, using StaticFiles for the root path (/) can lead to unexpected behavior, as it automatically serves index.html for the root directory.
Why index.html is Served Instead of Custom HTML
According to the [Starlette documentation](https://www.starlette.io/static-files/), StaticFiles has an html option that, when set to True, automatically loads index.html for directories if such a file exists.
Solution: Mount StaticFiles to a Different Path
To correctly render your custom HTML file on the root path, mount StaticFiles to a different path, such as /static:
from fastapi import FastAPI from fastapi.staticfiles import StaticFiles app = FastAPI() app.mount("/static", StaticFiles(directory="static"), name="static")
Mounting Order Matters
The order in which you mount StaticFiles and define your endpoints is crucial. If you mount StaticFiles after defining your root endpoint, the root endpoint will take precedence and the custom HTML file will be served.
Remove html=True Option
If you want to serve different HTML files dynamically and have additional endpoints, it's recommended to remove the html=True option from StaticFiles and use FastAPI's [Templates](https://fastapi.tiangolo.com/templates/) instead.
Conclusion
By addressing the ordering and configuration of StaticFiles, you can serve your custom HTML file instead of index.html on the root path while also enabling additional API endpoints. Consider the html=True option carefully depending on your specific use case.
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Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

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Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

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Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


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